Why the price elasticity of demand is not constant along a straight-line demand curve

This week my ECONS101 class covered elasticities. The most important elasticity that we cover in that topic is the price elasticity of demand. The price elasticity of demand can be calculated as [Percentage change in quantity demanded]/[Percentage change in price], or in shorthand, [%ΔQd]/[%ΔP]. Because price and quantity demanded always move in opposite directions (because of the Law of Demand - when price goes up, people buy less, and when price goes down, people buy more), the price elasticity of demand is always a negative number.

One important aspect of the price elasticity of demand is the determination of whether demand is elastic or inelastic. Demand is elastic if the percentage change in quantity demanded is greater than the percentage change in price. In other words, the price elasticity of demand is greater than one (in absolute terms). Demand is inelastic if the percentage change in quantity demanded is less than the percentage change in price. In other words, the price elasticity of demand is less than one (in absolute terms).

Now, here's where things get a little tricky. A straight-line demand curve that is relatively more elastic will be flatter than a demand curve that is relatively less elastic. That seems pretty straightforward, but the word 'relatively' is important. That's because the price elasticity of demand is not constant for a demand curve that is a straight line. Although the slope of the curve does not change as we move along the demand curve, the price elasticity of demand does.

To see why, consider the straight-line demand curve shown in the diagram below. At the top of the demand curve, such as the point A, the quantity demanded is low and the price is high. As we move along the demand curve a little bit towards the point B, the percentage change in quantity demanded is going to be large (because it's a percentage of a small number), but the percentage change in price will be small (because it's a percentage of a large number). That means that the price elasticity of demand, [%ΔQd]/[%ΔP], will be a large number (because we're dividing a large number by a small number). So, at the top of the demand curve, demand is elastic.

Now, at the bottom of the demand curve, such as the point C, the quantity demanded is high and the price is low. As we move along the demand curve a little bit towards the point D, the percentage change in quantity demanded is going to be small (because it's a percentage of a large number), but the percentage change in price will be large (because it's a percentage of a small number). That means that the price elasticity of demand, [%ΔQd]/[%ΔP], will be a small number (because we're dividing a large number by a small number). So, at the top of the demand curve, demand is inelastic.

Now consider the same example, but with some numbers, as shown in the diagram below. As we move from point A to point B (at the top of the demand curve), the percentage change in quantity demanded is 100%, as we move from a quantity demanded of 1 to a quantity demanded of 2 (we can calculate this percentage change as [[2-1]/1]-1). [*] The percentage change in price is -10%, as we move from a price of $10 to a price of $9 (we can calculate this percentage change as [[9-10]/10]-1). So, the price elasticity of demand when we move from point A to point B is [100]/[-10] = -10. This is larger than one (in absolute terms), so demand when we move from point A to point B is elastic.

As we move from point C to point D (at the bottom of the demand curve), the percentage change in quantity demanded is 11.1%, as we move from a quantity demanded of 9 to a quantity demanded of 10 (we can calculate this percentage change as [[10-9]/9]-1). The percentage change in price is -50%, as we move from a price of $2 to a price of $1 (we can calculate this percentage change as [[1-2]/2]-1). So, the price elasticity of demand when we move from point C to point D is [11.1]/[-50] = -0.22. This is smaller than one (in absolute terms), so demand when we move from point C to point D is inelastic.

So, there you have it. Although the demand curve may be a straight line, and so the slope doesn't change, the price elasticity of demand does change. At the top of the demand curve, demand is elastic, while at the bottom of the demand curve, demand is inelastic. As we move down the demand curve, demand becomes progressively less elastic. And as we move up the demand curve, demand becomes progressively more elastic. That means that there is a point where the demand curve transitions from being elastic to inelastic. That point occurs exactly halfway along the straight-line demand curve. At that point, the price elasticity of demand will be exactly equal to -1, which we refer to as unitary elastic.

*****

[*] For simplicity, I'm not using the midpoint method for calculating the price elasticity of demand here. We'd get qualitatively very similar results if we did so.

Disney adopts a combination of menu pricing and block pricing for Disney+

My ECONS101 class covered price discrimination this past week. Menu pricing (or second-degree price discrimination) occurs when consumers are offered different options (that the firm knows appeal to consumers with different price elasticities of demand), and consumers select their preferred option. Specifically, the firm will offer a lower price to consumers who are more price-sensitive (those with a higher price elasticity of demand), and a higher price to consumers who are less price-sensitive (those with a lower price elasticity of demand).

So, it was interesting to read this story in the New Zealand Herald last week:

Disney+ has become the latest in a procession of streaming services to hike its rate - though those willing to live with fewer features can stick with the old pricing.

Disney+ currently costs $14.99 per month.

From members’ next billing period, the price will increase by 27 per cent to $18.99 as the service is renamed Disney+ Premium - while the pricing for those who choose to pay annually also increases by 27 per cent from $149.99 to $189.99.

But there will also be a new Disney+ Standard option, which will stay at $14.99 (or $149.99 annually) - but support for two screens at once (compared to the Premium plan’s four) and standard high definition (the Premium plan offers 4K or ultra high definition).

This is an example of Disney using menu pricing. The Disney+ Standard option has a lower price, and will appeal to more price-sensitive consumers, while Disney+ Premium will appeal to consumers who are less price-sensitive.

Interestingly, the annual subscription price also offers an example of block pricing, which I will be covering in class this week. Block pricing occurs when the firm charges a declining price on subsequent blocks of product. In this case, the monthly price for Disney+ Premium is $18.99. However, those who pay for the full year pay just $189.99. In effect, after the first ten months of the year, the last two months are free (for those paying the annual fee). In other words, the first block of ten months cost $18.99, and the second block of two months costs nothing. It is a similar story for Disney+ Standard ($14.99 for the first ten months, and then free for the last two months).

Block pricing tends to work best when demand is homogeneous (as I noted in this post). One way that firms like Disney can get homogeneous demand is to first use price discrimination to separate consumers into relatively homogeneous groups. So, the shift to menu pricing (offering Disney+ Standard and Disney+ Premium) will likely make the block pricing strategy even more effective (and more profitable) for Disney.

This week in research #16

Here's what caught my eye in research over the past week (a quiet week, as preparing for my Professorial lecture took up far too much of my attention):

• Wright and Nguyen (open access) have a Treasury Analytical Note on the effect of taxes and benefits on household incomes in New Zealand in 2018/19 which, among many other results, shows how much the benefit and transfer system reduces inequality
• Kirchmaier, Langella, and Manning (open access) find that crime tends to happen close to the offender’s residence because criminals face a high cost of commuting
• Granato et al. (open access) look at the impact of the Erasmus study abroad programme in Europe, and find a positive and significant impact on the final graduation marks of undergraduate students, although somewhat weirdly this effect is larger if the student studies abroad at a university that is lower quality than their home university (more evidence on the benefits of study abroad, to sit alongside this)

Higher inflation is modestly associated with higher income inequality

There is a fairly large literature looking at the relationship between inflation and income inequality. Some studies find that there is a positive correlation (more inflation is associated with more income inequality). Some studies find the opposite, a negative correlation (more inflation is associated with less income inequality). Still other studies find no relationship at all between (or, at least, no statistically significant relationship). So, what are we to make of this literature?

To the rescue comes this recent article by Andreas Sintos (University of Luxembourg), published in the journal Economic Systems (sorry, I don't see an ungated version online). Sintos presents a meta-analysis of 124 journal articles, containing 1767 estimates of the relationship between inflation and income inequality. Sintos distinguishes between two strands of the literature: (1) looks at how the level of inflation affects the level of income inequality (in other words, the variables are measured in levels); and (2) looks at how changes in inflation affect changes in income inequality (in other words, the variables are measured in differences). The difference is important. In my view, measuring the relationship in levels doesn't make a lot of sense. If you find that the relationship is positive, then that implies that, since inflation is generally positive, income inequality should be ever-increasing. That seems somewhat inconsistent with reality. In contrast, it seems to me that when the level of inflation changes, that might change inequality.

Anyway, Sintos finds that:

...once the correction for publication bias is made, we find that, on average, inflation has a (small-to-moderate) inequality increasing effect for both level and difference estimates...

In other words, inflation increases inequality (to the extent that we can attribute causality to these results - more on that later in this post). The bias-corrected average effect size ranges between 0.051 and 0.120 (which are interpreted as small and moderate effect sizes respectively). Sintos then goes on to investigate the study-level factors that are associated with the estimated relationship. For the result in differences (which I find more theoretically plausible):

...we find that ten regressors matter significantly for the underlying effect of inflation on income inequality in the primary studies... the BMA [Bayesian Model Averaging] results for difference estimates reveal a decisive effect for eight regressors: GDP deflator, Panel data, Time span, Log transformation, GDP growth, Financial development, Publication year, and Citations. Moreover, we find a strong effect for Trade openness and a weak effect for Education.

Specifically, studies that cover a longer time span, use log-transformed variables, and those that control for GDP growth, financial development, and trade openness find a more positive effect of inflation on inequality, as well as those studies that have attracted more citations. Studies that use the GDP deflator (rather than the change in the Consumer Price Index) as a measure of inflation, use panel data, and those that were published most recently, find a more negative effect (or a smaller positive effect) of inflation on inequality. A couple of things jump out from that. First, the fact that more recent studies, which we would expect to use more sophisticated methods and better-quality data, find smaller effects, should lead us to believe that the 'true' effect is somewhat smaller (less positive) than what Sintos finds on average. However, when Sintos goes on to simulate the effect that would be obtained from the theoretical 'best study', they find that:

The associated prediction, which represents the model average across the models estimated using BMA, is 0.275, with a standard error of 0.115 (95% CI 0.051–0.500), for level estimates, and 0.540, with a standard error of 0.236 (95% CI 0.077–1.002), for difference estimates.

This is somewhat larger than the bias-corrected average effects reported in the paper. That makes me wonder whether the assumption that studies are improving in quality over time actually holds. Could it be that more lower-quality studies, or perhaps studies with lower-quality data, are increasingly being published? We don't have a direct answer to that question, but the correlation matrix reported in Figure 2 in the paper suggests that more recent publications are less likely to use OLS regression, and more likely to control for the variables that have important effects (as noted above). So, I remain somewhat at a loss to explain why the 'best study' estimates are larger than the bias-corrected average effects.

Second, the fact that studies that report more positive results have attracted more citations should be a bit of a concern. The literature had a diversity of results, and while the bias-corrected average effect is positive, that in itself shouldn't lead researchers to cite papers with positive effects more than those with the opposite, or with null effects. There is clearly a bit of cherry picking going on in terms of what results are cited in the literature.

Finally, the results don't establish causality definitively. Many of the studies deal with endogeneity problems, but not all of the studies do. So, while we can tell a plausible causal story here, we can't be sure about it. Nevertheless, this paper is another model of reporting meta-analytic results, the second such paper that I've read this year (see here for my post about the other paper). Given the importance of meta-analysis for estimating the average effect across a literature as a whole, the trend towards clearer exposition and interpretation of the results of meta-analyses is very welcome.

What we can take away from this paper is that higher inflation is modestly associated with higher income inequality. Given the sheer number of things that appear to be correlated with inequality, it would be expecting too much for inflation to have a large effect. But nevertheless, when we consider income inequality, inflation (or change in the inflation rate) appears to be an important consideration.

In The Three Body Problem trilogy, Wallfacer Rey Diaz needed to better understand game theory

Regular readers of this blog may have noticed that I haven't posted a book review in a while. That's because I've been reading Cixin Liu's Three Body Problem trilogy (technically, the Remembrance of Earth's Past trilogy, an adaptation of which has just been released on Netflix as The Three Body Problem). I'm currently reading the second book, The Dark Forest.

Warning: Spoiler alert!

To give you some context, in the first book of the trilogy, Earth made contact with an alien civilisation, the Trisolarans. The Trisolaran fleet is currently on its way to Earth, in order to conquer us. Their homeworld is about to be destroyed, and their only hope of survival is to take over another planet. The fleet will take some 400 years to arrive, so Earth has some time to prepare. However, the Trisolarans have advanced technology, including deploying sophons, which are able to prevent Earth from conducting basic research in physics and other areas. So, Earth is stuck in a low-technology state, awaiting the arrival of the Trisolaran fleet. Even worse, the sophons can watch anything that happens on Earth and relay the information back to the Trisolarans, so Earth's preparations will be known to the Trisolaran fleet. To combat this, in the second book, Earth appoints four 'Wallfacers', who are given access to almost unlimited resources to execute plans that are known only to themselves, hidden from the rest of the Earth's population (and to the sophons, because the sophons can't read minds).

The second book of the trilogy is devoted to the Wallfacers and their plans (admittedly, I haven't finished reading it yet). I want to focus on the plans of Wallfacer Rey Diaz, whose plan involved planting large solar hydrogen bombs on Mercury, which when detonated would set off a chain reaction, destroying most of the solar system, including Earth. Diaz's plan was to negotiate with the Trisolaran fleet, warning them that if they didn't divert, Earth would be destroyed, sealing the fates of both the human and Trisolaran populations.

However, Wallfacer Rey Diaz's strategy is flawed. He needs to understand some basic game theory. To see why, consider the game shown in the payoff table below. The two players are Earth and the Trisolaran fleet (we'll assume that Diaz would choose strategy on behalf of Earth). Earth's two strategies are to blow up Mercury (detonate) or not. The Trisolaran fleet's two strategies are to continue to Earth, or divert. If Earth blows up Mercury, then Earth becomes extinct, regardless of what the Trisolaran fleet does. If Earth doesn't detonate Mercury, then Earth loses if the Trisolaran fleet continues, and wins if the Trisolaran fleet diverts. If the Trisolaran fleet diverts, they become extinct. If they continue to Earth, they become extinct if Earth blows up Mercury, but win if Earth does not.

To find the Nash equilibrium in this game, we use the 'best response method'. To do this, we track: for each player, for each strategy, what is the best response of the other player. Where both players are selecting a best response, they are doing the best they can, given the choice of the other player (this is the definition of Nash equilibrium). In this game, the best responses are:

1. If the Trisolaran fleet continues to Earth, Earth's best response is to not detonate (since losing is a better payoff than extinction [*]) [we track the best responses with ticks, and not-best-responses with crosses; Note: I'm also tracking which payoffs I am comparing with numbers corresponding to the numbers in this list];
2. If the Trisolaran fleet diverts, Earth's best response is to not detonate (since winning is a better payoff than extinction);
3. If Earth chooses to detonate, the Trisolaran fleet's best response is either option (since both payoffs are the same - extinction - both are best responses); and
4. If Earth chooses not to detonate, the Trisolaran fleet's best response is to continue to Earth (since winning is a better payoff than extinction).

Note that Earth's best response is always to choose not to detonate. This is their dominant strategy. A player would always choose to play their dominant strategy, because choosing the other strategy makes them unambiguously worse off. And the Trisolarans would know this. This is what Wallfacer Rey Diaz gets wrong in his strategy. Earth won't blow Mercury up, and the Trisolarans know this, so there is no leverage for Earth in the negotiations.

The Trisolaran fleet has a weakly dominant strategy. Notice that continuing to Earth is always the Trisolaran fleet's best response. However, diverting is a best response if Earth chooses to detonate. So, continuing to Earth is not always better for the Trisolaran fleet, but it is never worse than the other strategy.

The single Nash equilibrium occurs where both players are playing a best response (where there are two ticks), which is where all Earth chooses not to detonate, and the Trisolaran fleet continues to Earth. It is little wonder then, that when Rey Diaz's strategy was revealed, the Earth governments were not happy. Not only was his strategy imperilling the Earth to the same extent as the Trisolarans, it was a strategy that simple game theory shows would not have succeeded.

*****

[*] You may wonder what the difference between losing and extinction is. Earth could lose, but some humans remain alive as slaves, or otherwise escape the planet before the Trisolarans arrive. It's not a great outcome, but better than extinction.

This week in research #15

Here's what caught my eye in research over the past week:

• May, McGarvey, and Toshmatova (open access) identify gender differences in US graduate students' views on the professional climate in economics, focusing on stress and work/life balance, disciplinary climate in the profession, departmental climate, and the prevalence of sexual harassment
• Blake, Thomas, and Hess (with ungated earlier version here) find that making recreational marijuana legal at the state level increases applications to the three largest state public schools, which received on average a 54% increase in applications (but this should be considered alongside a negative impact on student performance)
• Gershenson, Holt, and Tyner (with ungated earlier version here) find that high teacher grading standards increase both contemporaneous student achievement in first-year algebra and performance in subsequent math classes (so grade inflation is likely actively harming students)
• Carpenter et al. (open access) find that payday lenders don't protect regional economies, and in fact reduce the dynamism of the economy be reducing entry and exit of firms
• Preston and Wright (open access) find that the gender gap in financial literacy begins well before adulthood in Australia (although I'm a little disappointed they didn't cite my work here, with ungated earlier version here)
• Gulek (with ungated earlier version here) finds that driving while fasting (during Ramadan) at rush hour is associated with a 25% increase in the probability of having a traffic accident (timely, with Ramadan happening right now)
• Ragni, Ippolito, and Masci find, for engineering students in Milan, a subtle rise in earned credits and a slight decrease in grade point averages for those exposed to hybrid teaching (not too dissimilar from earlier results - see this post and all the links at the end of it)
• Bertacchini, Revelli, and Zotti (open access) find that UNESCO world heritage listing has a significant impact on income and property prices in urban areas of Italy
• Houseworth and Fisher find a raw interracial marriage wage penalty for White male spouses and a raw interracial marriage wage premium for Black male spouses, with a larger penalty for White males and a smaller premium for Black males in states that were forced to allow interracial marriage by the US Supreme Court
• Fischer (open access) finds that when gasoline alcohol sales were prohibited at gas stations in the German state of Baden-Wuerttemberg, gasoline margins dropped by 5%
• Lin, Liu, and Zhou find using a gravity model of trade that COVID-19 led countries to trade more with countries they were geographically closer to
• Tandon uses data from Yemen to show that large policy changes or shocks cause individuals to change how they answer subjective wellbeing (life satisfaction, or happiness) questions in ways that have little to do with changes in objective wellbeing measures (not surprising, but another challenge to happiness data)
• Anaya and Zamarro (with ungated earlier version here) find that the gender gap in PISA test scores may be underestimated, because boys put less effort into the test than girls (which is related to this as well)

A final reminder that I am giving a Professorial Lecture at the University of Waikato next Tuesday (26 March), titled Beyond the Buzz: The Sobering Economics of Alcohol. There are still tickets available, and you can register here. There's no livestream, but the event will be recorded and available sometime afterwards.

The commercial landlord oligopoly in Raglan claims a high-profile victim

This week, my ECONS101 class has been covering market structures and market power. By definition, market power is the ability of a seller (or sometimes a buyer) to have control over market prices. The degree of market power that a seller (or buyer) has depends on the amount of competition in the market. A big component of competition is the contestability of the market - how easy it is for other sellers (or buyers) to enter the market. When a market is highly contestable, it is difficult for a seller to maintain high prices (and high profits) because other sellers will be able to easily enter the market, increasing competition and lowering prices. But when a market has low contestability, high prices and high profits are likely to persist for sellers.

So, I was interested to read this article in the Waikato Times today [*]:

Raglan business owners say a landlord monopoly in the small beach town is jacking up rents, forcing them out.

Prominent Raglan music venue and bar Yot Club will soon be up for sale because the owner Andrew Meek says he’s “had enough of the landlords”.

Other operators spoken to by the Waikato Times said there was a power imbalance between tenants and owners with some having seen up to 95% rent increases in less than a decade...

Meek wanted to sell his business and said if it didn’t sell, he would shut the Yot Club by May.

“I hope that someone else can find a way through to maybe deal with the landlords, to maybe have a better relationship with police and licensing.

“This place means a lot to the community and there’s nothing like this in Raglan.”...

A business owner in the town centre, who did not want to be named, said they can’t move anywhere else because of what they called a monopoly on commercial rents.

“This is our life and livelihood, so they know that we are not going to leave and run.

“So they keep increasing the rent and compared to the whole country, the rent here is way too high.”

They said the 60m2 shop was renting for over $55000 for a year - nearly double the same-sized property in Hamilton’s Te Rapa.

“Every two years or whatever the document says, they put up the rent and then they take a management fee as well.

Another small business saw more than 90% increase in rent in the last six years.

“My landlord basically says he can do whatever he wants.”

In downtown Raglan, a few commercial landlords own most of the properties. The commercial property market in Raglan is not a monopoly (in contrast to what the business owner quoted above says), but it is an oligopoly - a market with few sellers. That limits competition and grants some market power to the commercial landlords, which they can use to increase rents. To make matters worse, this is a market with low contestability. Even though rents are high, and commercial landlords are making high profits, there is limited land in downtown Raglan zoned for commercial uses. Since the existing commercial landlord oligopoly holds all (or most) of that property, it is difficult (if not impossible) for other commercial landlords to enter this profitable market and compete. Moreover, Raglan is a long way from the next nearest commercial area which, excluding Whatawhata, is probably the Dinsdale shopping centre in Hamilton, over 30 minutes away. So, there is little alternative for businesses in Raglan other than to deal with the existing commercial landlord oligopoly.

However, things are even worse for the Yot Club than for other tenants. An iconic venue like the Yot Club is known for its current location and setup, including the outdoor area. That gives the Yot Club owner even less bargaining power in negotiating with the landlord than other tenants, since other tenants are more likely to be willing and able to move to a new location (even if that new location is outside of Raglan entirely).

So, the commercial landlord oligopoly in Raglan has a lot of market power. The commercial property market in Raglan lacks contestability. The tenants are paying high rents (note the comparison in the quote above with rents in Te Rapa, where there will be much higher competition between commercial landlords, because there are many alternative commercial areas within Hamilton that a tenant may choose to locate in). The landlords are likely making high profits as a result of their market power.

Having said all that, there are meaningful limits to how high the landlords can push the commercial rents. If rents get too high, then the commercial tenants will start to walk away (exiting the market), as it becomes unprofitable to continue their operations. This appears to be exactly what is happening now. And given the extra challenges that the Yot Club faces in dealing with the landlords, it shouldn't be a surprise that they were one of the first tenants to exit.

*****

[*] In the interests of full disclosure, I was a member of District Licensing Committee panels that have twice declined to renew the alcohol on-licence for the Yot Club. On both occasions, the Committee's decision was overturned on appeal to the Alcohol Regulatory and Licensing Authority. If you're interested, you can read the Committee's decisions here and here, and the corresponding ARLA appeal decisions here and here (and for completeness, you can read a further ARLA decision here, in which the final two sentences are particularly telling). Despite any perceptions that may have formed to the contrary, I bear no ill will towards the Yot Club or its owner, as the tenor of this post should demonstrate.

What happiness data tells us about whether life is getting better or worse over time

If you believed everything you read online, or in the media, you might get the impression that that state of the world is not only bad, but getting worse over time. It's gotten so bad, that everything seems to be in crisis. If it was the case that life is getting worse over time, we would expect to be able to see this reflected in people's subjective evaluations of their wellbeing - that is, their reported happiness. If life is worse now, surely people are reporting being less happy?

That is the research question at the heart of this new working paper by Ruut Veenhoven (Erasmus University Rotterdam) and Silke Kegel (University of Konstanz). Veenhoven and Kegel look at the happiness data from the World Database of Happiness, Report on Average Happiness in Nations, tracking changes in happiness measures over time for countries where the data:

...cover at least 20 years and involve at least 10 data-points... This left us with 80 timeseries in 50 nations over ranges of 71 to 20 years in the period 1945-2021.

They then apply some fairly simple comparisons (average happiness at the end of the time-series compared with average happiness at the start of the time-series), and simple linear regressions, to identify time trends in average happiness. If life is getting worse over time, the time trend should be negative. Instead, they find that:

...average happiness changed significantly only in 37 nations, of which 26 changed to greater happiness and 11 to less, the average size of the chances being similar. So again, more rise than decline.

In their linear time trends analysis, there was very little evidence of decreasing happiness. As they note, 11 nations (and 19 time trends) were statistically significant and negative, compared with 26 countries (and 62 times trends) that were statistically significant and positive, while 35 countries (and 119 time trends) were not statistically significant at all.

And when you look at which countries and time trends are positive or negative, they results seem to make some intuitive sense. For example, Japan since the 1960s shows a significant positive increase in happiness, but Japan since the 1990s shows no significant change, consistent with improvements in wellbeing that occurred mainly from the 1960s to the 1980s. Venezuela since the 1990s shows a large negative change, consistent with the basket case that country has become over that time. Ireland since the 1980s shows a positive change. And so on.

What we can take away from this (provided we suspend disbelief of all happiness data, which should be a real concern - see here, and here, but for a counterargument see here), is that life may not be getting worse after all.

Causation vs. correlation in the relationship between ultra-processed food and mental health

The New Zealand Herald reported earlier this week:

According to an annual global report, if you’re after mental wellbeing and a flourishing life, you should pay attention to those who live in the Dominican Republic, Sri Lanka, Tanzania and Panama.

The report, by Sapiens Labs, is available here. However, it was this bit of the article that caught my eye:

According to Sapien Labs, adults’ risk of mental health challenges is four times lower if you have close family relationships - but wealthier countries were least likely to say they were close with many adult family members, at just 23 per cent...

Similarly, there is a strong body of research on the impact of processed food and a growing number of studies around technology use.

“We found that over half of those who eat ultra-processed food daily are distressed or struggling with their mental wellbeing, compared to just 18 per cent of those who rarely or never consume ultra-processed food,” the report stated. This is almost a three-fold increase.

I just talked about the difference between causation and correlation with my ECONS101 class a couple of weeks ago. Everything that Sapiens Labs has found is correlation. Sure, you can tell a plausible story about how ultra-processed foods lower mood and lead to worse mental wellbeing. However, there is also a plausible story going in the other direction (reverse causation) - people with worse mental health might comfort eat, thereby consuming more ultra-processed foods. Just because we observe a correlation between higher ultra-processed food consumption and lower mental wellbeing (a negative correlation), it doesn't mean that ultra-processed food consumption causes decreases in mental wellbeing.

Even worse than that, the report itself (but not the New Zealand Herald article) tries to suggest a link between higher consumption of single-use plastics and lower mental wellbeing. I'm not even sure that you can tell a plausible story linking those two variables in that direction - how would plastic straws, forks, and grocery bags make our mental health worse? This could well be spurious correlation. However, I'd be surprised if there is even a correlation there at all. Many countries (including New Zealand) have recently banned single-use plastics. Have we seen an immediate improvement in mental health in those countries? I thought not.

Just because two variables are moving together (either in the same direction, or opposite directions) that doesn't mean that changes in one variable are causing changes in the other one. No matter how much you might want them to, or how much you are looking for a simple explanation. Correlation is not the same as causation.

This week in research #14

Here's what caught my eye in research over the past week:

• Badunenko and Popova (open access) find that in Germany from 1985 to 2015, while income inequality has increased significantly, migration did not contribute to that increase
• Adabor (open access) finds that the COVID-19 support payment in Australia is positively associated with gambling, with larger effects on male gamblers and online gamblers (I guess gambling is a normal good?)
• Hadavand, Hamermesh, and Wilson show that economics publishing proceeds much more slowly than in the natural sciences, and more slowly than in the other social sciences and finance, and that much of the lag is the result of authors taking a long time to complete revisions (time for economists to stop complaining, and start revising-and-resubmitting their papers!)
• Eugster and Uhl (open access) show that sentiment data, based on 730,000 news articles between Q1 2003 and Q4 2021, is able to forecast inflation more accurately than a naive random walk
• Tomlin (open access) finds in a field experiment that tenant applicants that reveal their pronouns are less likely to receive a response from a landlord, regardless of whether the pronouns signalled that the applicant was cisgender or transgender
• Brander et al. (open access) estimate from a survey that households would be willing to pay US$79 per year to conserve marine turtles, implying that taking policy action to conserve, manage and protect marine turtles would generate US$55 billion in value

Finally, I am giving a Professorial Lecture at the University of Waikato on Tuesday 26 March. This public lecture is titled Beyond the Buzz: The Sobering Economics of Alcohol, and it builds on my last 15-plus years of research on the social impacts of alcohol. All new professors must give one of these lectures, and I've been dodging it for over a year! The event is free (and they'll even feed you beforehand), but to go you need to register here. I'm not just adding a sales pitch when I say that tickets have been selling fast, so if you want to come along you need to get your ticket sooner rather than later.

One way that dynamic pricing in retail or fast food is different from Uber's surge pricing

I had an interesting discussion after yesterday's post about the difficulty of regulation to prevent dynamic pricing. It highlighted a key difference between Uber surge pricing and otherwise similar dynamic pricing in retail or fast food contexts.

As I noted in this 2015 post:

...surge pricing is used to manage excess demand - when the quantity of Uber rides demanded by users exceeds the quantity of rides available from drivers at that time. In other words, there is a shortage of available Uber drivers.

Surge pricing solves a market problem - a shortage of Uber drivers. Increasing the price of Uber rides induces more drivers to make themselves available, increasing the quantity of Uber rides supplied. This reduces the shortage of Uber drivers, and makes it easier for Uber customers to find a ride (albeit, a more expensive ride).

The dynamic pricing I've been blogging about this week doesn't work that way. It doesn't solve a market problem. There is no shortage of Wendy's burgers, where raising the price would induce Wendy's to offer more burgers for sale, reducing the shortage.

So, while you could argue that Uber's surge pricing may make some consumers better off (since they don't have to wait as long for a ride), it's more difficult to make that case for Wendy's dynamic burger pricing. As I noted on Monday, maybe the burgers will be cheaper in periods of low or elastic demand, making consumers who are buying at those times better off. But the burgers will be more expensive in periods of high or inelastic demand, making those consumers worse off.

Now, none of this means that the appropriate response is for government to regulate dynamic pricing. As I noted yesterday, that regulation would likely break a bunch of things that we wouldn't want broken, and may simply end up with consumers all worse off as a result. However, that just means that there isn't anything easy that government can do to intervene. Consumers themselves have some power here too. And indeed, that's exactly what happened with Wendy's. After consumer backlash, they walked back any plans to roll out dynamic burger pricing.

I still think it's coming eventually. Obviously, just not yet.

Read more:

• The future of fast food may include surge pricing
• The difficulty of regulation to prevent dynamic pricing

The difficulty of regulation to prevent dynamic pricing

It feels a bit like I jumped the gun on yesterday's post about surge pricing in fast food, because overnight the Financial Times published an article by Rana Faroohar on surge pricing (gated), where she wrote:

But I suspect that even more change — and more demands for tougher, clearer cut regulation — will come as online business models make their way into old-fashioned businesses where people are simply accustomed to much clearer rules. As consumers become more aware of how the tricks of surveillance capitalism are being used in businesses that they first used in the physical world, it may draw attention to the need for clear, straightforward rules — applying the existing laws of the physical world to online customer protection.

I’d love to see the FTC, for example, use its rulemaking power to stipulate a “thou shalt not discriminate” statue that makes it illegal to charge people different prices for different goods, no matter how and where they are buying them. What’s illegal in the physical world should also be illegal in the online world. This would put the onus on companies to prove that they are not causing harm, rather than forcing regulators to create a distinct and more complex system for a particular industry.

Tougher, clearer cut regulation is certainly possible here, but I don't think most consumers would be happy about the obvious unintended consequences. Depending on how the regulations are worded, there are a lot of things that consumers would be giving up in order to have price parity for everyone. 

Let's start with making price discrimination (charging consumers difference prices for the same good or service) illegal. This would be the most heavy-handed regulation, and have the most severe unintended consequences. Haggling with your appliance store or car dealer? Probably no longer possible, because that would lead to some consumers (the non-hagglers) paying a higher price than others (the hagglers). Free trials? Loyalty card discounts? Special deals for subscribers? Daily deals websites (like Grabone)? All gone. Quantity discounts? By-two-get-one-half-price? Coffee cards that give you your tenth coffee for free? It's hard to see how any form of block pricing would survive this regulation. 'No claims discounts' for insurance? Probably also gone.

So, eliminating price discrimination entirely is obviously problematic and it would be difficult for policy-makers to write exceptions for those cases that wouldn't create big loopholes that sellers could exploit. Moreover it isn't clear that eliminating price discrimination would result in lower prices for consumers. If government makes Gold Card discounts for seniors, or discounts for students or staff members, illegal, then it seems to me that prices go up, not down.

What about more focused regulation? What if the government simply made charging different prices at different times of the day, or different days, illegal? That would be the end of 'early bird' price discounts. Late-comers end up paying a higher price than the early birds, so they would be regulated out of existence. Similarly flights could no longer be cheaper if purchased well in advance. Cheap matinees for shows or movies? Happy hour drinks? Also gone. Could market stalls or bakeries still sell the leftover goods at the end of the day for a discount? It seems unlikely.

So, the regulation would have to be even more specific than that. What about regulation that prevents rapid or frequent changes in price. Let's put aside the difficulty of how this would be policed. Would firms have to apply to the Commerce Commission before they were allowed to change price? Or would there be limits on how often prices can be changed (like the law in Scotland that prohibits changing the price of drinks within 72 hours of the last price change [*]). Anyway, how would this most focused regulation deal with auction sites? Not only is it next to impossible to have auctions where every buyer pays the same price, it is next to impossible to ensure that auctions for the same item don't fluctuate widely in price, even within the same day. You could carve out an exception for financial markets, but you couldn't have an innovative firm like The Beer Exchange (although given that at least one site has recently closed down, maybe it isn't a successful business model anyway).

There's a reason that governments don't already regulate dynamic pricing. It's in the too-hard basket, and for good reason. 'Fixing' problems caused by dynamic pricing would break so many other things that consumers actually benefit from. As another example, it's not clear to me that government should be making Gold Card discounts for seniors, or discounts for students or staff members, illegal.

Current discrimination laws already protect consumers from discrimination on the basis of protected characteristics, such as gender, ethnicity, sexual orientation, and so on. It's not clear what we gain if the government institutes further protections from dynamic pricing. But as consumers, we could certainly lose a lot.

*****

[*] This led to a whole different set of unintended consequences, with happy hours stretching out to become happy days!

Read more:

• The future of fast food may include surge pricing

The future of fast food may include surge pricing

Back in 2017, I wrote a post about the future of supermarket pricing, concluding that:

...surge pricing is coming. When you see the traditional price sticker replaced by a small LCD or LED display, you'll know it has probably arrived.

So, I was not surprised to read this USA Today story from a couple of weeks ago:

More fast-food joints, restaurant chains and brick-and-mortar retailers are taking advantage of technological advances to tap into real-time trends and swiftly adjust prices, sometimes in seconds.

It’s a tempting proposition for big businesses that can dramatically increase revenue with slight pricing changes.

Wendy’s was the latest to say it will fluctuate prices of chicken nuggets or a classic chocolate Frosty based on demand.

In a conference call earlier this month, Wendy’s CEO Kirk Tanner said the fast-food chain would experiment with dynamic pricing as early as next year...

“Beginning as early as 2025, we will begin testing more enhanced features like dynamic pricing and daypart offerings, along with AI-enabled menu changes and suggestive selling,” he said. “As we continue to show the benefit of this technology in our company-operated restaurants, franchisee interest in digital menu boards should increase, further supporting sales and profit growth across the system.”

So, how does this dynamic pricing work? When demand is high, or when consumers have fewer alternatives (so that demand is less elastic), the profit-maximising price is higher. So, in those periods of high or inelastic demand, the firm can increase profits by raising the price. On the other hand, when demand is low, or when consumers have more alternatives (so that demand is more elastic), the profit-maximising price is lower. In those periods of low or elastic demand, the firm can increase profits by lowering the price. Changing the price to better match demand conditions offers a way for the firm to increase profits both when demand is high, and when demand is low. This is essentially how Uber's surge pricing works (as I noted here).

Of course, constantly changing prices comes with problems. There are menu costs for the firm, which are the direct costs of changing prices (they are called menu costs because, when a restaurant changes prices, it needs to print new menus). But there are also more strategic problems for the firm. Second, changing prices creates uncertainty for consumers, and if they are uncertain what the price will be on a given day, perhaps they choose not to purchase (in other words, the cost of price discovery for consumers makes it not worth their while to find out the price). Third, consumers may see such price changes as unfair. This came out in research by Nobel Prize winner Daniel Kahneman and others (and described in his book Thinking, Fast and Slow). That research showed that consumers are willing to pay higher prices when sellers face higher costs (consumers are willing to share the burden), but consumers are unwilling to pay higher prices when they result from higher demand - they see those price increases as unfair.

All of that might explain why Wendy's almost immediately changed its plans after customer outcry. They issued a statement that said:

We have no plans to do that and would not raise prices when our customers are visiting us most.

Maybe not now, but perhaps sometime in the future. Dynamic pricing is coming to fast food. Watch this space.

[HT: Marginal Revolution] 

It's not a surprise that medical practices might try to avoid sick patients

The New Zealand Herald reported yesterday:

Some GP clinics which are nearly at capacity say they are selecting which patients they enrol, raising concerns they could be discriminating against some groups or excluding difficult patients.

A survey of 220 general practice staff in New Zealand found four out of five had stopped or limited their enrolments over the previous three years.

Some staff reported they had selectively enrolled patients by refusing those with high health needs - a practice known as “cream-skimming”.

Associate Professor Mona Jeffreys, an epidemiologist at Victoria University, said previous studies had focused narrowly on how many practices were open or closed, without considering how many had limited their enrolment and how...

“Some are only taking family members, some are taking people who are new to the area. But some are making decisions based on health, which means that people who have … poorer health are less likely to be enrolled because practices know there is a greater burden.”

The research that this article was based on, published in the New Zealand Medical Journal, is here (gated). Now, medical practices making a decision to exclude patients with poorer health might seem a bit surprising. However, it is quite rational behaviour on the part of those practices. That's because, as this Bay of Plenty Times story from yesterday notes:

[Pāpāmoa Pines Medical Centre’s co-owner and partner Pamela] Sheahan said government funding for GPs through the capitation model was “not fit for purpose” and needed to be “significantly overhauled”.

Capitation-based payments are based on the numbers of people enrolled with individual general practices who belong to a primary health organisation population, the Te Whatu Ora website says.

“We’re paid for four visits per year per patient. If you get children and older people, they come to the GP far more than four times … sometimes up to 20 times a year,” Sheahan said.

“We just don’t get paid for any of those visits so we have to claw that back by charging patients over the counter the additional fees.”

Sheahan said the only way the business made money – apart from government funding – was charging patients.

A rational (and profit-maximising, or at least loss-minimising) medical practice will take on a patient as long as the benefits (to the practice) of that patient exceed the costs. The benefit the practice receives is the government capitation funding plus any patient fees. The capitation funding covers the cost of the first four visits for any patient. The practice will break even if every patient visited exactly four times per year (and the practice charged no fees). The practice will make a profit from patients that visit fewer than four times per year (typically the most healthy patients), and from patient fees charged to those that visit four or fewer times per year.

However, patients that visit more than four times per year pose a problem. Patient fees might be enough to ensure that the practice breaks even on patients visiting maybe six times per year (as an example). Patients that visit more times than those (typically the patients in the poorest health) will be a net loss to the practice. For those patients, the cost of providing care exceeds the benefits that the practice receives (in terms of capitation funding plus patient fees).

A rational and profit-maximising medical practice would therefore make an assessment of each potential patient, and take on only those patients that are likely to visit four or fewer times per year (or maybe six or fewer times). They would reject any patients that would be likely to visit more often than that. This is the 'cream-skimming' that the first article mentions.

Fortunately, medical practices are not quite that cold-hearted. There will certainly be some cross-subsidisation, with the profits that the practice receives from some patients covering the shortfall on the care provided to other patients. However, there are limits to the amount of cross-subsidisation that can occur. Eventually, the profits from the healthy patients are overwhelmed and at that point the medical practice has few options left. They can raise the patient fees, they can limit their exposure to patients in poor health (as noted above), or they can shut down.

It would be easy to blame the medical practices here, but it really isn't their fault. The health system, and in particular the funding model and funding level for general practice, are the real problem (see here and here, for example). If the government continues the chronic underfunding of general practice, then we will simply continue to see more of this rational behaviour from medical practices.

[Update: More evidence of cream skimming from the New Zealand Herald]

This week in research #13

Here's what caught my eye in research over the past (clearly, very active) week:

• Exley and Nielsen (with ungated earlier version here) use experimental data to show that the gender gap in confidence (with women being less confident than men) causes evaluators to form overly pessimistic beliefs about women (happy International Women's Day, I guess?)
• Chapple (open access) finds that previous estimates of a pre-European-contact Māori population of 100,000 may be underestimated by more than half
• Bertola (open access) shows theoretically that opportunities to re-take an exam generally increase the probability of eventually passing a given threshold at given competence, but decrease preparation for exams (no surprises there)
• Parshakov et al. (open access) find a statistically significant beauty premium among Major League Soccer players, with players with greater facial symmetry being paid a higher salary
• On a somewhat similar note, Pieper and Schulze look at the social media popularity of all female soccer players who took part in the European Championship 2022, and find that while beauty has no statistically significant direct effect on players’ market values, it indirectly affects their values through the effect on social media popularity
• Basiglio, Foresta, and Turati (with ungated earlier version here) find a positive association between  impatience and crime, using data from the National Longitudinal Survey of Youth 1997 in the US
• Elass (open access) uses data from the UK, France and Finland, and a novel microsimulation method, and finds that disparities in the gender wage gap between these countries are driven by occupational segregation (clustering of men and women in different occupations) and public spending on families
• Abrahams finds that on average, firms didn't cut wages when the minimum wage in St. Louis fell in nominal terms in 2017 (interesting because we rarely see the effects of decreases in the minimum wage)
• Reis, Godinho de Matos, and Ferreira (open access) find that batch DNS filtering of copyright-infringing websites leads to a significant reduction in Internet traffic, which they argue represents a significant decrease in internet piracy
• Cotofan, Dur, and Meier (with ungated earlier version here) look at US General Social Survey data, and find that experiencing bad macroeconomic circumstances between the ages of 18 and 25 strengthens anti-immigration attitudes for life
• Collins and Lundstedt (with ungated earlier version here) use Swedish data to show that more granular grading scales discourage students, with students less likely to graduate from high school, from academic high school tracks, and from STEM and art high school tracks, and less likely to enrol in STEM courses at university
• Goulão et al. (open access) find using a field experiment that job applications with a photo manipulated to make a person seem overweight results in fewer callbacks for men (compared with a photo showing normal weight), and that this effect is especially pronounced in female dominated occupations, but the results are opposite for women

Book review: The Worldly Philosophers

I just finished reading Robert Heilbroner's excellent book The Worldly Philosophers. I forget who recommended it to me, but perhaps it was a mention in this blog by Dianne Coyle. Anyway, the book was first published in 1953 and has been through seven editions, with the last edition (which was the one I read) published in 1999. No doubt, Heilbroner would have written further editions, but he passed away in 2005.

The book is a great primer on the history of economic thought. It doesn't have as broad a coverage as New Ideas from Dead Economists (which I reviewed here) or The Economics Book (which I reviewed here). Heilbroner limits consideration to the truly big names in economics - Adam Smith, Thomas Malthus, David Ricardo, John Stuart Mill, Karl Marx, Alfred Marshall, Thorsten Veblen, John Maynard Keynes, and Joseph Schumpeter. And there is a fairly large cast of supporting actors. But what the book lacks in breadth it more than makes up in depth, as well as in the sheer quality of the writing. Heilbroner writes in an easy and engaging style, and large parts of the book read more like a historical novel than an exposition of some of the great thinkers in economics. For example, consider this passage, part of a longer section introducing the reader to Keynes:

But this is only a sample of his many-sidedness. He was an economist, of course - a Cambridge don with all the dignity and erudition that go with such an appointment; but when it came to choosing a wife he eschewed the ladies of learning and picked the leading ballerina from Diaghilev's famous company. He managed to be simultaneously the darling of the Bloomsbury set, the cluster of Britain's most avant-garde intellectual brilliants, and also the chairman of a life insurance company, a niche in life rarely noted for its intellectual abandon. He was a pillar of stability in delicate matters of international diplomacy, but his official correctness did not prevent him from acquiring a knowledge of other European politicians that included their mistresses, neuroses, and financial prejudices. He collected modern art before it was fashionable to do so, but at the same time he was a classicist with the finest private collection of Newton's writings in the world. He ran a theater, and he came to be a Director of the Bank of England. He knew Roosevelt and Churchill and also Bernard Shaw and Pablo Picasso. He played bridge like a speculator, preferring a spectacular play to a sound contract, and solitaire like a statistician, noting how long it took for the game to come out twice running. And he once claimed that he had but one regret in life - he wished he had drunk more champagne.

As you can see, Heilbroner gives much insight into the private lives of the great economists (or worldly philosophers, as the book is titled), which you wouldn't normally see in a book on the history of economic thought. Heilbroner does a good job of linking together the key sites of agreement and disagreement, as well as the development of economic theory and philosophy over time. However, he is efficient enough in his writing that the economists' lives outside of economics can be given far more colour. Indeed, he makes them come alive in a way that I hadn't appreciated before, and it was those parts of the book that I especially enjoyed. Of course, that could just be because the history of economic thought was mostly not new to me.

The book is not without its flaws though. He repeats a discredited idea that Thomas Carlyle labelled economics the 'dismal science' after reading the work of Thomas Malthus, when in fact Carlyle was decrying that economists were not in favour of reintroducing slavery in the West Indies (see Wikipedia on this point). Also, I wonder about this point:

Purely by way of curious illustration, it is reported that among the New Zealand Maoris you cannot ask how much food a bonito hook is worth, for such a trade is never made and the question would be regarded as ridiculous.

Heilbroner is relying there on the doctoral work of the ethnologist Raymond Firth from the 1920s (I have Firth's book on the economics of Māori, but haven't read it as yet), but I strongly suspect that work has not aged well, and trade was certainly not unknown to Māori even earlier than Firth's writing.

Nevertheless, I did really enjoy this book. If you are looking for a nice gentle introduction to the history of economic thought, with a bit more history and biography, and a bit less of the economics, this would be a great book to try.

Missed opportunity by the New Zealand Herald on school fees and student performance

I was interested to hear the New Zealand Herald's Front Page podcast this morning, which focused on two issues: (1) the high and increasing cost of private schools; and (2) the close correlation between student performance at high schools (as measured by NCEA pass rates) and a measure of socioeconomic status (the Equity Index, or EQI, which replaced the decile ranking system at the start of last year). The first issue was interesting but uninspiring. It's hard to feel sorry for the rich families who have to pay even more to send their kids to private school. You could try to argue that it makes private school even more unaffordable for low-income families. But, newsflash! Private school is already unaffordable for those families. When something is already so expensive that some people can't afford to buy it, making it even more expensive doesn't make those people any worse off.

What I want to focus on is the second issue (which is based on this paywalled article). As New Zealand Herald head of data Chris Knox noted in the podcast, there is a very strong correlation between NCEA (and University Entrance) pass rates and the Equity Index (in fact, a student group project in BUSAN205 last year showed this quite clearly). Higher socio-economic schools have higher pass rates. On top of that, Knox noted that private schools have higher pass rates than public schools.

The combination of those last two results makes me wonder. What is the cost, to parents, of sending a child to a school with a higher pass rate? In other words, what is the parental willingness-to-pay for an additional percentage point of pass rate? It would actually be relatively easy to work out the correlation between school fees and NCEA pass rates, controlling for the EQI and other relevant school-level variables. All we would need is data on pass rates, EQI, and other school variables (all available from the Education Counts website), and data on school fees (which might need to be hand-collected from school websites - I don't think that data is collated anywhere [*]). The results of this analysis would provide a lower-bound on how much parents are willing to pay for additional pass rates (it is a lower bound, because it is what they actually pay - they might be willing to pay even more, if the school was bold enough to charge higher fees).

This was definitely a missed opportunity by the Herald team. Their results are interesting but, aside from showing correlation rather than any causal relationship (as my ECONS101 class covered last week), they don't show us something that would be of great interest to economists. And not only economists. No doubt schools themselves would be interested to know how much parents are willing to pay for higher pass rates. That way, schools that have high pass rates would feel justified in charging higher fees.

*****

[*] That's the main reason why I haven't already done this analysis. Education Counts has some data on school donations (that is, fees), but it's really just a collation of how many schools in each region have opted into the government scheme that gives them higher funding if they make school fees voluntary for parents.

Reason to be sceptical about trends in adult height in India

A couple of years ago, I read this 2021 article by Krishna Kumar Choudhary, Sayan Das, and Prachinkumar Ghodajkar (Jawaharlal Nehru University), published in the journal PLoS ONE (open access). I've been holding off blogging about it, in the hopes that I could get one of my past PhD students interested in exploring this data and testing the claims further, but no one seems too interested (or, at least, they're too busy doing other exciting things). So, here we go.

Choudhary et al. use data across multiple waves of the Indian National Family Health Survey, and track trends in adult height in Indian provinces over the period from 1998-99 (NFHS-II) to 2015-16 (NFHS-IV). They found that:

Between NFHS-III and NFHS-IV, the average height of women in the age group of 15–25 showed a decline by 0.12 cm [95% CI, -0.24 to 0.00, p-0.051] while in the 26–50 years age strata it demonstrated significant improvement in the mean height by 0.13 cm [95% CI, 0.02 to 0.023, p-0.015]. However, Between NFHS III and IV, the average height of women in the poorest wealth index category registered a significant decline [-0.57cm, 95% CI, -0.76 to -0.37, p-0.000]. Between NFHS III and IV, the average height of Scheduled Tribe (ST) women in the age group of 15–25 years also exhibited a significant decline by 0.42 cm, [95% CI, -0.73 to -0.12, p-0.007]. Among men, between the two surveys, both the age groups of 15–25 years and 26–50 years showed significant decline in average height: 1.10 cm [95% CI, -1.31 to -.099 cm, p-0.00] and 0.86 cm [95% CI, -1.03 to -0.69, p-0.000], respectively.

You read that right. According to Choudhary et al., people in India are shorter in 2015-16 than they were in 2005-06 (NFHS-III). The distribution of mean height by age for those two surveys is given in Figure 4 in the paper:

Notice that, within every age group, the mean height is lower in 2015-16 than in 2005-06. However, here is where I have severe doubts about this analysis. The sample of Indian men in 2015-16 is (for the most part) the same as the sample of men ten years younger in 2005-06. So, if you compare a given age group's mean height in 2015-16, it shouldn't be too much different from the mean height of the age-group ten years younger in 2005-06. And yet, that doesn't appear to be true for almost any comparison in Figure 4. Look at the mean height for any age on the bold line in the figure, move to the right by ten years, and you will never intersect with the dashed line.

So, one of three things is going on here. Either, Indian men are shrinking, there are measurement errors that are changing over time, or there are compositional changes in the sample that explain the differences. It seems unlikely that people are genuinely shrinking. So, that leaves the other two explanations.

Although the NFHS is a 'nationally representative survey', there are serious issues with the survey (as documented by Sylvia Karpagam here). That suggests that measurement error might be at play. However, it would have to be measurement error that occurs in a way that heights were either systematically under-reported in NFHS-IV, systematically over-reported in NFHS-III, or both. That does seem a little unlikely.

What about compositional changes? There may be differences in survey coverage (see here), especially between women in NFHS-II (which only included ever-married women) and NFHS-III (which included both ever-married women and never-married women). However, it is less clear that the changes affected men in the sample. On the other hand, this bit from the Choudhary et al. caught my attention:

The samples drawn for analysis of women’s height were 83876 out of 90303 from NFHS-II, 121728 out of 138592 from NFHS-III, and 700602 out of 749344 from NFHS-IV. For men’s height, sample of 66468 out of 74396 from NFHS- III and 105783 out of 126543 from NFHS-IV were drawn.

Notice that the sample for women increases nearly six-fold between NFHS-III and NFHS-IV, but the sample for men increases only by about 60 percent. That might be accurate, but it strikes me as odd, unless men are only surveyed in a subset of households, and the proportional subset that were selected was different (and much smaller) in NFHS-IV than in NFHS-III. That could cause a change in the composition of the survey sample, and might explain the results for men (less so for women). Anyway, there is reason to doubt these results, and it might be an interesting project for a suitably motivated Honours or Masters student to follow up on.

This week in research #12

 Here's what caught my eye in research over the past week:

• Milanovic (with ungated earlier version here) documents three eras of global inequality: (1) between 1820 and 1950, when inequality increased both between and within countries; (2) between 1950 and the 1990s, where inequality was high; and (3) since the 1990s, when inequality has fallen mostly thanks to increases in income in Asia, and particularly China (see here or here or here for more of Milanovic's work on related topics)
• Masset, Terrier, and Livat (open access) find that wines that use more feminine descriptors sell for similar prices to wines that use more masculine descriptors, but are perceived as having more limited ageing potential (in other words, more wine bullshit, like here or here)
• Connolly et al. (open access) find that allowing Sunday beer sales in Connecticut had a short-term impact on beer sales, but no impact on the number of grocery retailers or liquor stores
• Cattaneo et al. summarise the papers in a special issue of the Journal of Econometrics in honour of Jianqing Fan, devoted to data science in economics and finance (the papers themselves tend to be quite technical, but the summary, including on the work of Fan, seems good)